We address the PCS (physical carrier sensing) threshold selection problem for dense wireless loca... more We address the PCS (physical carrier sensing) threshold selection problem for dense wireless local area networks (WLANs). This important network parameter determines the spatial reuse permitted by the CSMA/CA protocol, which consequently determines the interference level. Using Poisson Point Processes (PPP) from stochastic geometry, we obtain a closedform expression for PCS threshold selection. Our primary aim is to find the PCS threshold value that improves the spatial density of throughput (SDT). Assuming a Rayleigh fading channel, we derive the PCS threshold as a function of node density and path loss exponent, parameters that are global and easily measured. That is, we determine the optimal PCS threshold based on the fundamental parameters of the network without requiring channel knowledge of each link. To assess the impact of the proposed method, simulation results reveal gains in throughput density over the conventional and the random selection methods.
A new decentralized hypothesis detection framework is developed, where local sensors are memoryle... more A new decentralized hypothesis detection framework is developed, where local sensors are memoryless, receive independent observations, and minimum feedback from the fusion center. In addition to the standard criterion of minimizing detection delay under error probability constraints, an additional constraint on the number of communications between local sensors and the fusion center is introduced here. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both error probabilities and on the number of communications. Unfortunately, optimality requires derivation of time-delay distributions of reports to the fusion center and solution of nonlinear equations. Under certain approximations, a Poisson arrival model is shown to yield a tractable solution. The efficiency of the proposed algorithm is quantified analytically in comparison to centralized detection and is shown to be in agreement with simulation results.
Densification is an essential paradigm for future wireless networks in the unlicensed millimeter-... more Densification is an essential paradigm for future wireless networks in the unlicensed millimeter-wave (mmWave) band. Despite the promises of multi-gigabit data rates in mmWave due to wide spectrum availability, high node density could lead to severe interference and channel contention that reduce spatial reuse and overall throughput performance. To that effect, this paper investigates an approach to improve spatial average of throughput by optimizing the carrier sensing thresholds that govern the effectiveness of the channel access protocols. We consider a network with two radio access technologies (RATs) coexisting in the unlicensed mmWave spectrum. Using stochastic geometry tools to model network density, channel access protocols and spatial statistical average of throughput, closed-form expressions are proposed for selecting the carrier sensing thresholds without requiring frequent channel sounding to obtain network information. Numerical results obtained through simulation demonstrate the effectiveness of optimizing the carrier sensing thresholds to account for node density, transmit power and the mmWave propagation characteristics.
Network densification provides coverage by reducing load factor and path loss between user equipm... more Network densification provides coverage by reducing load factor and path loss between user equipments (UEs) and the serving base stations (BSs) or access points (APs) [1]. To increase capacity, a wide range of spectrum in diverse bands could be harnessed by deploying dense multiple radio access technologies (RATs). This benefit of densification is contingent on the interference level generated by high density coexisting nodes and multi-RATs in the same spectrum. To this effect, we seek to optimize the maximum node density that should coexist in a network to maximize throughput performance for high density networks. This is important because increasing network density (densification) increases interference and contention, and subsequently degrades aggregate performance. Using stochastic geometry tools, a special case of two co-existing RATs is considered. Due to the unplanned nature of APs and/or BSs deployments, the nodes are assumed to be realizations of Poisson point processes (PPPs). Numerical results reveal that optimizing node density results in throughput gains for mid to high density networks.
2015 IEEE Global Communications Conference (GLOBECOM), Dec 1, 2015
Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices a... more Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices are required to detect a change in spectrum occupancy as quickly as possible. A new decentralized change detection framework is developed for cognitive wireless networks, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and false alarm rate, we introduce a new constraint: the number of communications between local sensors and the fusion center. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both false alarm rate and number of communications. Simulation results are investigated to explore the tradeoffs in parameter choices of the proposed algorithm.
Emerging wireless technologies require the support for a massive number of low data rate battery ... more Emerging wireless technologies require the support for a massive number of low data rate battery operated devices. With this motivation, this paper employs widely linear processing in simultaneous wireless information and power transfer (SWIPT) systems. By considering the transmission of low-rate one-dimensionally modulated signals in the downlink of a SWIPT broadcast channel, a widely linear zero forcing (ZF) precoder and a widely linear minimum mean square error (MMSE) precoder are proposed which are capable of offering service to more users than the number of transmit antennas. Semi closed-form solutions are obtained for both scenarios and iterative dual ascent based algorithms are presented to obtain the transmit precoding (beamforming) matrices. Simulation results demonstrate the effect of widely linear processing in increasing the number of information decoding devices.
Motivated by the poor performance of the existing transmit beamforming methods in low signal to n... more Motivated by the poor performance of the existing transmit beamforming methods in low signal to noise ratio regime, and assuming that the knowledge of the modulation type could result in a more intelligent design of beamformers, this paper proposes a transmit beamforming method based on the concept of minimum probability of error (MPE) beamforming. We calculate the error probability of each user in the downlink of a multiuser scenario and design an objective function based on the weighted sum of these error probabilities. We take a convex optimization approach to solve this ill-behaved nonconvex optimization problem. It is shown that by minimizing this objective function, the performance of the system could be dramatically improved.
Dense deployment of wireless local area networks (WLANs) is part of the next generation Wi-Fi and... more Dense deployment of wireless local area networks (WLANs) is part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. However, dense deployment of WLAN access points (APs) faces increased interference and uncoordinated association of user stations (STAs) with APs, which degrade network throughput. To assess the potential of improving uplink throughput in the presence of interference using AP association coordination, we propose an association optimization algorithm that matches STAs to APs in dense WLAN (DWLAN). While existing cell breathing approaches suggest tuning of APs' beacon powers for association control, the proposed approach utilizes uplink signal- interference-noise ratio (SINR) of stations (STAs) to coordinate STA-AP association. In order to further coordinate interference and increase spatial reuse, an algorithm is proposed to adjust the clear channel assessment (CCA) threshold of the 802.11 MAC protocol in each AP cell to address the problem of overlapped basic service set (OBSS) that degrades overall network throughput. Performance evaluation reveals that our SINR-based AP association coordination and CCA threshold adjustment schemes achieve significant increase in per-user throughput in a DWLAN.
2015 IEEE Global Communications Conference (GLOBECOM), 2014
Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices a... more Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices are required to detect a change in spectrum occupancy as quickly as possible. A new decentralized change detection framework is developed for cognitive wireless networks, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and false alarm rate, we introduce a new constraint: the number of communications between local sensors and the fusion center. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both false alarm rate and number of communications. Simulation results are investigated to explore the tradeoffs in parameter choices of the proposed algorithm.
2016 Annual Conference on Information Science and Systems (CISS), 2016
The problem of detecting a change in distribution of a sequence of independent and identically di... more The problem of detecting a change in distribution of a sequence of independent and identically distributed (IID) random variables is addressed. Unlike previous approaches to sequential change detection, which assume a known initial probability density function (PDF) for the sequence, in this paper we address the case where the initial distribution of the sequence is unknown. An optimal stopping approach based on Bayesian hypothesis testing with exponential delay cost is proposed. The tradeoffs among average detection delay, probability of false alarm and probability of detecting a change in the incorrect direction are investigated. It is shown that the proposed test's probability of change detection in the incorrect direction can be made arbitrarily small without significantly increasing average detection delay for change times larger than a minimum value determined by the hypothesis testing problem itself. The proposed test also has a recursive algorithm to track the minimum risk hypotheses with fixed complexity per sample. Simulation results confirm the derived properties and reveal that the average delay, after an initial transient period, approaches that of the CUSUM test, which is delay-optimal if the initial state were known.
We address the PCS (physical carrier sensing) threshold selection problem for dense wireless loca... more We address the PCS (physical carrier sensing) threshold selection problem for dense wireless local area networks (WLANs). This important network parameter determines the spatial reuse permitted by the CSMA/CA protocol, which consequently determines the interference level. Using Poisson Point Processes (PPP) from stochastic geometry, we obtain a closedform expression for PCS threshold selection. Our primary aim is to find the PCS threshold value that improves the spatial density of throughput (SDT). Assuming a Rayleigh fading channel, we derive the PCS threshold as a function of node density and path loss exponent, parameters that are global and easily measured. That is, we determine the optimal PCS threshold based on the fundamental parameters of the network without requiring channel knowledge of each link. To assess the impact of the proposed method, simulation results reveal gains in throughput density over the conventional and the random selection methods.
A new decentralized hypothesis detection framework is developed, where local sensors are memoryle... more A new decentralized hypothesis detection framework is developed, where local sensors are memoryless, receive independent observations, and minimum feedback from the fusion center. In addition to the standard criterion of minimizing detection delay under error probability constraints, an additional constraint on the number of communications between local sensors and the fusion center is introduced here. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both error probabilities and on the number of communications. Unfortunately, optimality requires derivation of time-delay distributions of reports to the fusion center and solution of nonlinear equations. Under certain approximations, a Poisson arrival model is shown to yield a tractable solution. The efficiency of the proposed algorithm is quantified analytically in comparison to centralized detection and is shown to be in agreement with simulation results.
Densification is an essential paradigm for future wireless networks in the unlicensed millimeter-... more Densification is an essential paradigm for future wireless networks in the unlicensed millimeter-wave (mmWave) band. Despite the promises of multi-gigabit data rates in mmWave due to wide spectrum availability, high node density could lead to severe interference and channel contention that reduce spatial reuse and overall throughput performance. To that effect, this paper investigates an approach to improve spatial average of throughput by optimizing the carrier sensing thresholds that govern the effectiveness of the channel access protocols. We consider a network with two radio access technologies (RATs) coexisting in the unlicensed mmWave spectrum. Using stochastic geometry tools to model network density, channel access protocols and spatial statistical average of throughput, closed-form expressions are proposed for selecting the carrier sensing thresholds without requiring frequent channel sounding to obtain network information. Numerical results obtained through simulation demonstrate the effectiveness of optimizing the carrier sensing thresholds to account for node density, transmit power and the mmWave propagation characteristics.
Network densification provides coverage by reducing load factor and path loss between user equipm... more Network densification provides coverage by reducing load factor and path loss between user equipments (UEs) and the serving base stations (BSs) or access points (APs) [1]. To increase capacity, a wide range of spectrum in diverse bands could be harnessed by deploying dense multiple radio access technologies (RATs). This benefit of densification is contingent on the interference level generated by high density coexisting nodes and multi-RATs in the same spectrum. To this effect, we seek to optimize the maximum node density that should coexist in a network to maximize throughput performance for high density networks. This is important because increasing network density (densification) increases interference and contention, and subsequently degrades aggregate performance. Using stochastic geometry tools, a special case of two co-existing RATs is considered. Due to the unplanned nature of APs and/or BSs deployments, the nodes are assumed to be realizations of Poisson point processes (PPPs). Numerical results reveal that optimizing node density results in throughput gains for mid to high density networks.
2015 IEEE Global Communications Conference (GLOBECOM), Dec 1, 2015
Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices a... more Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices are required to detect a change in spectrum occupancy as quickly as possible. A new decentralized change detection framework is developed for cognitive wireless networks, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and false alarm rate, we introduce a new constraint: the number of communications between local sensors and the fusion center. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both false alarm rate and number of communications. Simulation results are investigated to explore the tradeoffs in parameter choices of the proposed algorithm.
Emerging wireless technologies require the support for a massive number of low data rate battery ... more Emerging wireless technologies require the support for a massive number of low data rate battery operated devices. With this motivation, this paper employs widely linear processing in simultaneous wireless information and power transfer (SWIPT) systems. By considering the transmission of low-rate one-dimensionally modulated signals in the downlink of a SWIPT broadcast channel, a widely linear zero forcing (ZF) precoder and a widely linear minimum mean square error (MMSE) precoder are proposed which are capable of offering service to more users than the number of transmit antennas. Semi closed-form solutions are obtained for both scenarios and iterative dual ascent based algorithms are presented to obtain the transmit precoding (beamforming) matrices. Simulation results demonstrate the effect of widely linear processing in increasing the number of information decoding devices.
Motivated by the poor performance of the existing transmit beamforming methods in low signal to n... more Motivated by the poor performance of the existing transmit beamforming methods in low signal to noise ratio regime, and assuming that the knowledge of the modulation type could result in a more intelligent design of beamformers, this paper proposes a transmit beamforming method based on the concept of minimum probability of error (MPE) beamforming. We calculate the error probability of each user in the downlink of a multiuser scenario and design an objective function based on the weighted sum of these error probabilities. We take a convex optimization approach to solve this ill-behaved nonconvex optimization problem. It is shown that by minimizing this objective function, the performance of the system could be dramatically improved.
Dense deployment of wireless local area networks (WLANs) is part of the next generation Wi-Fi and... more Dense deployment of wireless local area networks (WLANs) is part of the next generation Wi-Fi and standardization (802.11ax) efforts are underway. However, dense deployment of WLAN access points (APs) faces increased interference and uncoordinated association of user stations (STAs) with APs, which degrade network throughput. To assess the potential of improving uplink throughput in the presence of interference using AP association coordination, we propose an association optimization algorithm that matches STAs to APs in dense WLAN (DWLAN). While existing cell breathing approaches suggest tuning of APs' beacon powers for association control, the proposed approach utilizes uplink signal- interference-noise ratio (SINR) of stations (STAs) to coordinate STA-AP association. In order to further coordinate interference and increase spatial reuse, an algorithm is proposed to adjust the clear channel assessment (CCA) threshold of the 802.11 MAC protocol in each AP cell to address the problem of overlapped basic service set (OBSS) that degrades overall network throughput. Performance evaluation reveals that our SINR-based AP association coordination and CCA threshold adjustment schemes achieve significant increase in per-user throughput in a DWLAN.
2015 IEEE Global Communications Conference (GLOBECOM), 2014
Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices a... more Spectrum sensing constitutes a key functionality of a cognitive radio (CR), and sensing devices are required to detect a change in spectrum occupancy as quickly as possible. A new decentralized change detection framework is developed for cognitive wireless networks, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and false alarm rate, we introduce a new constraint: the number of communications between local sensors and the fusion center. This communication metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. The proposed detection scheme minimizes detection delay with constraints on both false alarm rate and number of communications. Simulation results are investigated to explore the tradeoffs in parameter choices of the proposed algorithm.
2016 Annual Conference on Information Science and Systems (CISS), 2016
The problem of detecting a change in distribution of a sequence of independent and identically di... more The problem of detecting a change in distribution of a sequence of independent and identically distributed (IID) random variables is addressed. Unlike previous approaches to sequential change detection, which assume a known initial probability density function (PDF) for the sequence, in this paper we address the case where the initial distribution of the sequence is unknown. An optimal stopping approach based on Bayesian hypothesis testing with exponential delay cost is proposed. The tradeoffs among average detection delay, probability of false alarm and probability of detecting a change in the incorrect direction are investigated. It is shown that the proposed test's probability of change detection in the incorrect direction can be made arbitrarily small without significantly increasing average detection delay for change times larger than a minimum value determined by the hypothesis testing problem itself. The proposed test also has a recursive algorithm to track the minimum risk hypotheses with fixed complexity per sample. Simulation results confirm the derived properties and reveal that the average delay, after an initial transient period, approaches that of the CUSUM test, which is delay-optimal if the initial state were known.
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